Result Filters

Search: Analysis[Title] AND B[Title] AND cell[Title] AND subsets[Title] AND following[Title] AND pancreatic[Title] AND islet[Title] AND cell[Title] AND transplantation[Title] AND patient[Title] AND type[Title] AND 1[Title] AND diabetes[Title] AND cytometric[Title] AND fingerprinting[Title]

Analysis of Bcellsubsetsfollowingpancreaticisletcelltransplantation in a patient with type1diabetes by cytometricfingerprinting.

1Department of Pathology and Laboratory Medicine, University of Pennsylvania School of Medicine, Philadelphia, PA 19104, USA.

Abstract

Manual gating of bivariate plots remains the most frequently used data analysis method in flow cytometry. However, gating is operator-dependent and cumbersome, particularly with the increasing complexity of modern multicolor immunophenotyping data. A method that can remove operator bias, enable systematic and thorough analysis of complex high-dimensional data, correlate temporal changes in different subsets and lead to biomarker discovery is needed. Here we apply such a method, called cytometricfingerprinting (CF), to data obtained on peripheral blood B cells from an adult patient with type-1diabetes who underwent pancreaticislettransplantation. We establish that CF can be used to analyze longitudinal trends in immunophenotypic data, and show that results from CF are comparable to those obtained with traditional gating methods. Both methods reveal the appearance of transitional B cells and subsequent accumulation of more mature B cells following immunosuppression and transplantation. This pattern is consistent with a temporally ordered process of Bcell auto-reconstitution. We also show the comparative efficiency of fingerprinting in recognizing relative changes in Bcellsubsets with respect to time, its ability to couple the data with statistical methods (agglomerative clustering) and its potential to define novel subsets.

This figure shows the process of binning and fingerprinting. For illustrative purposes, we use only 2 dimensions and 16 bins.(A) Binning is accomplished recursively, using the aggregate of the two baseline samples for this illustration. In the first step, CD38 is found to have the most variance. The data are split at the CD38 median (thick black horizontal line) into two halves. (The lower half contains bins 1–8 and the upper half contains bins 9–16.) Each of these halves is split again in the direction of maximum variance among the events in each bin (blue lines), and then again (green lines) and once more (red lines). The resulting bins, numbered 1 – 16, are shown. Events are plotted as dots and colored according to their bin membership. The bin and dot coloration match the color scheme provided in (C).(B) Two samples are compared with the bin boundaries determined in (A). The left panel is one of the two baseline samples and the right panel shows the sample on day 155. The number of events in each of these bins is counted to create the two fingerprints expressing comparison with the baseline aggregate. Events in bins with more than 2-fold increase relative to aggregated baseline are plotted as pink dots. All other events are plotted as black dots.(C) Fingerprints are plotted on a normalized scale. The left panel corresponds to the baseline sample (as in (B)) and the right panel corresponds to the day 155 sample. The y-axis denotes fold difference relative to the aggregated baseline, where a value of 1 indicates identity and is shown as a horizontal yellow line. The x-axis indicates the bin numbers and the bins are colored as shown in (A). The dot-dashed lines indicate the values of bins with 2-fold increased numbers of events compared to the baseline model. Note that bins 15 and 16 in the right panel exceed the 2-fold threshold.

(A) CD27 vs. CD38 analysis performed on B cells (CD19+ lymphocytes) at baseline (shown is one of the two baseline time points). Arrows indicate the major Bcellsubsets: transitional (CD27−CD38++), naïve mature (CD27−CD38+), mature activated (CD27+CD38+) and resting memory (CD27+CD38−). Percentages of B cells are provided within each gated region.(B) CD27 vs. CD38 analysis performed on B cells at days 8, 29 and 71 post-transplantation. Percentages of B cells are provided within each gated region.

Stacked bars show the progression over time of Bcellsubsets, analyzed as shown in . Each bar represents a single time point.(A) Percentage of B cells. The proportion of CD19+ lymphocytes is plotted as a function of the time point post-transplant (in days).(B) Absolute Bcellsubsets. The absolute B lymphocyte count (B cells per microliter of whole blood) is plotted as a function of the time point post-transplant (in days). The two leftmost bars in both panels represent baseline data obtained one month apart while the patient was on the transplant waiting list.

(A) Cytometric Fingerprints. Each row corresponds to the fingerprint of an individual sample relative to the aggregated baseline binning model. The x-axis is the bin number. The y-axis indicates the fold increase relative to the aggregated baseline. The tick marks for the y-axes represent fold intervals of 2. The horizontal bar under the histogram plots provides color-coding for the bin members that are plotted in panel B. The dashed horizontal lines in each fingerprint indicate the 4-fold threshold of increased density relative to the baseline model.(B) Bivariate plots of highlighted CF histogram bins. At time points d155, d182, d273, d365 and d450 there were fingerprint bins that exceeded the threshold of a 4-fold increase (refer to Panel A). Bivariate plots of CD27 vs. CD38 expression are shown for these time points. The black dots represent all of the events at the indicated time point. The dots highlighted with color correspond to events in the >4-fold increased bins in the corresponding fingerprint. The bivariate plots indicate a progression from less mature (CD27−, CD38++) to more mature (CD27−, CD38+) phenotypes as a function of time post-transplant.

Each panel represents a summary of phenotypic changes at a given time point relative to the aggregated baseline. Each line, from bottom to top of an individual panel, corresponds to a single Bcell. Lines are generated by connecting the parameter values for each cell. Red lines indicate cells in bins that are increased by at least 4-fold relative to baseline. Blue lines indicate cells in bins that are decreased at least 4-fold relative to baseline. The y-axis gives the six parameters (FSC, SSC, CD10, CD38, CD19 and CD27). The x-axis for each of the parameters is scaled from the minimum to the maximum observed values for that parameter. BL = baseline. FSC = forward scatter. SSC = side scatter.

Temporally correlated bins were clustered as described in section 2.4 and plotted as a dendrogram. The y-axis represents the distance (computed as described in the text) at which clusters merge. The dendrogram was parsed into 7 clusters, numbered 1 through 7. The same cluster numbers are used in .

Each panel represents one of the clusters shown in the dendrogram in . The left side of each panel provides a plot of the fold change relative to baseline for the cluster as a function of time. Each thin line in this plot represents one bin in the cluster, while the thick black line represents the average fold change for all of the bins in the cluster. Numbers above the average fold change line denote the percentage of B cells in the cluster at each time point. For example, cluster number 4 at day 155 contains 15.2% of the B cells. The right side of each panel shows a bivariate plot of CD38 vs. CD27 fluorescence intensity (gated on CD19+ lymphocytes). The plots shown correspond to the time points at which the average cluster density is maximal (e.g., d155 for cluster number 4). The black dots represent the B cells in the cluster. The pseudocolor background denotes all of the B cells at the corresponding time point. Panels are ordered from top to bottom and left to right chronologically according to the time at which their average density peaks.